390 | END‐OF‐TREATMENT PET/CT COMPLETE REMISSION IS HIGHLY PROGNOSTIC IN NODAL PERIPHERAL T‐CELL LYMPHOMA: AN AUSTRALASIAN‐CANADIAN COLLABORATIVE STUDY
Notice bibliographique
Résumé
J. Kuruvilla and G. Gregory equally contributing author. Introduction: The prognostic value of imaging following frontline treatment of nodal peripheral T-cell lymphoma (PTCL) has been demonstrated (Gleeson, EHA 2022; Cottereu, J Nucl Med 2018; El-Galaly, AJH 2015); however, its significance specific to each nodal subtype is unknown. Our study aims to assess the prognostic value of end-of-treatment (EOT) imaging across PTCL subtypes. Methods: Retrospective review of the Australasian Lymphoma and Related Diseases Registry (LaRDR) from January 2016 to December 2023 and the Princess Margaret Cancer Centre (PMCC) lymphoma database from November 2011 to March 2024. Inclusion criteria: adults 18-years or over, receiving frontline therapy for PTCL-not otherwise specified (PTCL-NOS), T follicular helper-cell (TFH) lymphoma [angioimmunoblastic T-cell lymphoma, PTCL with TFH phenotype, follicular T-helper-cell lymphoma] and anaplastic large cell lymphoma (ALCL). Outcomes included the prognostic value of EOT 18F FDG positron emission tomography (PET) with low-dose computed tomography (CT) or contrast-enhanced CT on progression-free survival (PFS) defined from diagnosis to progressive disease (PD)/death, and overall survival (OS) defined from diagnosis to death. Results: 466 patients (pts) were included (LaRDR 294, PMCC 172). Baseline characteristics are shown in Table 1. 92% of pts received anthracycline-based primary treatment. Median follow-up was 48 m (range 40–49). No difference in 36 m PFS (LaRDR: 29% [95% CI: 22–36] versus PMCC: 23% [95% CI: 17–30], p = 0.29) and OS (LaRDR: 55% [95% CI: 48–61] versus PMCC: 59% [95% CI: 51–67], p = 0.22) was found between the 2 cohorts. 289 pts had EOT imaging reports available (PET: 251, CT: 38). Imaging response and Deauville score (DS) at EOT are shown in Table 1. Of the 289 pts, EOT PET/CT CR versus no CR had a 36 m PFS of 44% (95% CI: 36–52) versus 7% (95% CI: 3–12), p < 0.001 and a 36 m OS of 78% (95% CI: 71–84) versus 27% (95% CI: 19–36), p < 0.001. EOT DS 1–2 or 3 was associated with superior PFS (p < 0.001) and OS (p = 0.02) compared with those achieving a DS 4–5 (DS only available in a subset of pts, n = 83). Achieving an EOT CR versus not achieving a CR was predictive of superior PFS and OS at 24 m in all subtypes; PTCL-NOS (p < 0.001, p = 0.004), TFH lymphoma (p < 0.001, p < 0.001) and ALCL (p < 0.001, p < 0.001). The positive predictive value (PPV, ability of lack of CR on EOT PET to predict death) at 30 m was 67% (95% CI: 57–78) and negative predictive value (NPV, ability of a CR on EOT PET to predict survival) at 30 m was 81% (95% CI: 73–87). Conclusion: Achieving a CR on EOT PET/CT is highly prognostic of PFS and OS in nodal PTCLs. Our analysis also confirms similar prognostic value in subtypes PTCL-NOS, TFH lymphoma and ALCL. A high NPV but modest PPV on EOT imaging for predicting survival and death is also shown. While outcomes for those not achieving CR at EOT are poor, outcomes for those achieving CR are also suboptimal. Integration of measurable residual disease analysis with imaging techniques may improve prediction of clinical outcomes. Keywords: non-Hodgkin; PET-CT; aggressive T-cell non-Hodgkin lymphoma Potential sources of conflict of interest: D. Rodin Consultant or advisory role: Needs Inc. Stock ownership: Needs Inc. A. Prica Honoraria: Kite/Gilead, AstraZeneca, Abbvie S. Opat Consultant or advisory role: AbbVie, AstraZeneca, BeiGene, Janssen, Novartis Honoraria: AbbVie, AstraZeneca, BeiGene, Gilead. Janssen, Merck Other remuneration: Research Funding (to institutions LARDR and Monash Health) AbbVie, AstraZeneca, BeiGene, Gilead, Janssen, Novartis, Pharmacyclics, Roche, Takeda E. Wood Other remuneration: Research funding to my institution from: Abbvie, Amgen, Antengene, AstraZeneca, Beigene, Bristol-Myers Squibb, CSL Behring, Gilead, GSK, Janssen-Cilag, Novartis, Pfizer, Roche, Sanofi and Takeda. Research support (provision of study drug) for a clinical trial, from Sobi. E. Hawkes Consultant or advisory role: AstraZeneca, Janssen Oncology, Merck Sharpe & Dohme, Gilead, Bristol Myer Squibb, Novartis, Beigene, Link Healthcare, Specialised therapeutics, regeneron, Roche Educational grants: AstraZeneca Other remuneration: Speakers Bureau—Regeneron, Abbvie, Roche, AstraZeneca; research funding—AstraZeneca, Roche, Bristol Myer Squibb, Merck KgA, Gilead, Janssen-Cilag, Abbvie. M. Crump Consultant or advisory role: Kite/Gilead J. Kuruvilla Consultant or advisory role: Lymphoma Canada, Abbvie, Bristol Myers Squibb, Gilead/Kite, Merck, Roche, Seattle Genetics, Karyopharm Honoraria: Abbvie, Bristol Myers Squibb, Amgen, AstraZeneca, Beigene, Genmab, Incyte, Janssen, Karyopharm, Merck, Novatis, Pfizer, Roche, Seattle Genetics Other remuneration: Grants from Canadian Cancer Society Research Institution (CCSRI), Canadian Institutes of Health Research, Leukaemia and lymphoma Society Canada, Princess Margaret Cancer Foundation, AstraZeneca, Kite, Merck, Novartis, Janssen, Roche. G. Gregory Consultant or advisory role: Roche, Merck, AstraZeneca, Gilead/Kite, Prelude Therapeutics, Clinigen Other remuneration: Research funding to institution from BeiGene, AbbVie
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».